AIMC Topic: Humans

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Resonator Networks, 2: Factorization Performance and Capacity Compared to Optimization-Based Methods.

Neural computation
We develop theoretical foundations of resonator networks, a new type of recurrent neural network introduced in Frady, Kent, Olshausen, and Sommer (2020), a companion article in this issue, to solve a high-dimensional vector factorization problem aris...

Self-evoluting framework of deep convolutional neural network for multilocus protein subcellular localization.

Medical & biological engineering & computing
In the present paper, deep convolutional neural network (DCNN) is applied to multilocus protein subcellular localization as it is more suitable for multi-class classification. There are two main problems with this application. First, the appropriate ...

Role of machine learning in gait analysis: a review.

Journal of medical engineering & technology
Human biomechanics and gait form an integral part of life. The gait analysis involves a large number of interdependent parameters that were difficult to interpret due to a vast amount of data and their inter-relations. To simplify evaluation, the int...

Deep learning for identifying corneal diseases from ocular surface slit-lamp photographs.

Scientific reports
To demonstrate the identification of corneal diseases using a novel deep learning algorithm. A novel hierarchical deep learning network, which is composed of a family of multi-task multi-label learning classifiers representing different levels of eye...

Image segmentation of plexiform neurofibromas from a deep neural network using multiple b-value diffusion data.

Scientific reports
We assessed the accuracy of semi-automated tumor volume maps of plexiform neurofibroma (PN) generated by a deep neural network, compared to manual segmentation using diffusion weighted imaging (DWI) data. NF1 Patients were recruited from a phase II c...

Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study.

BMC medical research methodology
BACKGROUND: Interest in models for calculating the risk of death in traumatic patients admitted to ICUs remains high. These models use variables derived from the deviation of physiological parameters and/or the severity of anatomical lesions with res...

Artificial Intelligence for Automated Overlay of Fundus Camera and Scanning Laser Ophthalmoscope Images.

Translational vision science & technology
PURPOSE: The purpose of this study was to evaluate the ability to align two types of retinal images taken on different platforms; color fundus (CF) photographs and infrared scanning laser ophthalmoscope (IR SLO) images using mathematical warping and ...

Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study.

PloS one
BACKGROUND & AIMS: Liver ultrasound scan (US) use in diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) causes costs and waiting lists overloads. We aimed to compare various Machine learning algorithms with a Meta learner approach to find the best ...